Systems and methods for automatic change request management using similarity metric computations

Abstract

Systems and methods for managing change requests are disclosed. A system for managing change requests may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving, from a client device, a change request; routing the change request to a first similarity determination pipeline, based on the first classification, identifying an implementation device; and transmitting the change request to the implementation device. The first similarity determination pipeline may be configured to: extract at least one first request element from the change request; determine a first group of change requests based on the at least one first extracted request element; determine a first similarity metric between the change request and the first group of change requests; and determine a first classification of the change request based on the first similarity metric.

What is claimed is: 
     
       1. A method for managing change requests, comprising:
 receiving a change request; 
 extracting a first request element from the change request; 
 determining a first similarity metric between the received change request and a second change request based on the extracted first request element; 
 determining a first classification of the received change request based on the first similarity metric; 
 determining an implementation device to implement the received change request based on the first classification; and 
 transmitting the received change request to the implementation device. 
 
     
     
       2. The method of  claim 1 , wherein the change request includes at least one optioned text field and one freeform text field. 
     
     
       3. The method of  claim 1 , wherein extracting the first request element comprises applying at least one of a stop word removal, a case conversion, a lemmatization, or a typographical correction to the received change request. 
     
     
       4. The method of  claim 1 , wherein extracting the first request element comprises applying a term frequency-inverse document frequency feature extraction algorithm to the received change request. 
     
     
       5. The method of  claim 1 , wherein a second classification of the second change request was previously determined based on an extracted second request element of the second change request. 
     
     
       6. The method of  claim 5 , wherein determining the first similarity metric comprises comparing the extracted first request element and the extracted second request element. 
     
     
       7. The method of  claim 6 , wherein the comparing includes performing at least one of: word-to-word matching, word-to-synonym matching, word ordering similarity identification, or word combination similarity identification. 
     
     
       8. The method of  claim 6 , wherein the comparing includes determining a similarity score based on a result of the comparing. 
     
     
       9. The method of  claim 8 , wherein the similarity score is based on a count or a percentage of at least one of: word-to-word matches, word-to-synonym matches, word ordering matches, or word combination matches. 
     
     
       10. The method of  claim 8 , wherein the first classification is based on whether the similarity score exceeds a threshold. 
     
     
       11. The method of  claim 5 , wherein determining the first similarity metric comprises computing at least one distance between a first numeric-space representation of first characters of the extracted first request element and a second numeric-space representation of second characters of the extracted second request element. 
     
     
       12. The method of  claim 11 , wherein computing the at least one distance includes at least one of: inserting, deleting, substituting, or transposing characters or groups of characters. 
     
     
       13. The method of  claim 11 , wherein computing the at least one distance includes computing a Euclidean or a Hamming distance. 
     
     
       14. The method of  claim 11 , wherein the at least one distance is computer according to at least one of: a Levenshtein distance algorithm, a Jaro-Winkler distance algorithm, a Sorensen similarity distance algorithm, or a fuzzy distance algorithm. 
     
     
       15. A system for managing change requests, comprising:
 at least one processor; and 
 a non-transitory computer-readable medium containing a set of instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
 receiving a change request; 
 extracting a first request element from the change request; 
 determining a first similarity metric between the received change request and a second change request based on the extracted first request element; 
 determining a first classification of the received change request based on the first similarity metric; 
 determining an implementation device to implement the received change request based on the first classification; and 
 transmitting the received change request to the implementation device. 
 
 
     
     
       16. The system of  claim 15 , wherein extracting the first request element comprises applying at least one of a stop word removal, a case conversion, a lemmatization, or a typographical correction to the received change request. 
     
     
       17. The system of  claim 15 , wherein a second classification of the second change request was previously determined based on an extracted second request element of the second change request. 
     
     
       18. The system of  claim 17 , wherein determining the first similarity metric comprises comparing the extracted first request element and the extracted second request element. 
     
     
       19. The system of  claim 18 , wherein the comparing includes performing at least one of: word-to-word matching, word-to-synonym matching, word ordering similarity identification, or word combination similarity identification. 
     
     
       20. The system of  claim 18 , wherein:
 the comparing includes determining a similarity score based on a result of the comparing; 
 the similarity score is based on a count or a percentage of at least one of: word-to-word matches, word-to-synonym matches, word ordering matches, or word combination matches; and 
 the first classification is based on whether the similarity score exceeds a threshold.